From gut feel to hard data – the HR analytics journey at HSCIC


The Health and Social Care Information Centre (HSCIC) proves that it only takes a spreadsheet and some determination to get started in HR analytics.

keyboard-stethThere isn’t a manual for what I’m doing at the moment. So I just get in there and I stay focused.

This “learning by doing” approach to HR analytics is a great way to find out about HR analytics, according to Alan Sewell, HR manager at the Health and Social Care Information Centre (HSCIC).

The HSCIC was set up by the UK Department of Health to provide information, data and IT systems for to the NHS in the UK. So, collating and analyzing data is in its DNA. But it was a different story within its internal HR department, where decisions were often made on gut feel rather hard data. Sewell explains:

No one really had any sense of the numbers…when we talked about the numbers, we’d say ‘roughly this amount’ or ‘give or take’ that kind of language.

Sewell took on the mission last year to educate himself and the rest of the 45-strong HR team about analytics:

It was frustrating, because we had so much data around us everywhere and we just chose not to use it. And I didn’t really understand why.

But becoming a data-driven HR department is not something that happens overnight. There were plenty of challenges facing Sewell, such as the fact that  he was a team of one and the organization was embroiled in a major transformation project, which meant priorities were a moving target and systems and processes were in flux.

While he didn’t have a project team, he did have the full backing and support of his line manager and director. And although he is a one-man team, he is not isolated from the rest of the HR department: .

I’m not in just in a room on my own providing data.

With a blank sheet in front of him, Sewell first created a vision statement of what he wanted to achieve. It’s an obvious first step, but it has proved an invaluable aid for helping him focus on what’s important against the chaotic backdrop created by the organizational transformation.

He also keeps a close eye on where they are on the analytics maturity model. At the moment, the team has moved beyond the starting point of making opinion-based decisions. But it is still at the level of dealing with data and metrics. The world of ‘true’ analytics and insight still lies ahead, but as he points out:

You can’t go from having nothing to insight overnight. It takes a really, really long time, especially if you want to do it through other people.

Performance reporting

Sewell chose first to look at the obvious areas of performance and resourcing.  Crating performance reports had been difficult and it took a lot of manpower to pull together the right data. So, Sewell put in the time to talk to teams and find out their priorities and help them find the data needed to help with reporting.

Simply having visibility into the data has brought a range of benefits, including reducing case investigation time, reducing time to recruit and improving data quality. And the benefits have been as much about engagement as pure performance measures. 

But there’s still a lot more insight to squeeze out of the data, says Sewell:

We had some performance success, but we still have loads of data that we still don’t use.

What’s important is ta the team members are now motivated to start asking their own questions and refining the metrics, rather than ask Sewell to do it.

It was a similar story with recruitment. There was a lack of any kind of standard reporting and limited visibility. By collating basic data on recruitment campaigns, number of applications, start-date for campaigns and so on, the team has far more visibility into the process.  Now it is easy to report on time to recruit and candidate split.

So when feedback from managers suggested that the recruitment process was too long, which meant that some good candidates were snapped up by other organization, the HR team were able to show how the data supported this hunch. Process changes were duly made, cutting the recruitment time from 90 days to 65 days as a result.

But the journey to get to this point has been rather different from what Sewell expected:

I thought I’d be spending my time getting involved in bringing data in from different systems, combining it together  – and it just didn’t happen.  I wasn’t spending my time really analysing a lot of the data. Instead I was spending my time meeting people, setting up systems, dealing with data quality issues, asking people to collect more information or data and trying to engage the team generally. So I started to think that this HR analytics business is probably a lot broader than the analytics piece.

Building relationships within the HR team with HR operations, recruitment and administration has been vital. But it was just as important to forge partnerships outside the HR enclave with IT and finance.  Creating close links with finance is particularly important, says Sewell:

They’re quite similar to use in terms of data we both hold a lot of data and we hold a lot of people data. But in the past we both produced reports in isolation.

And sometimes that data did not match. When finance data points to salaries going up, but HR data points to headcount going down, there are naturally going to be questions asked by senior managers.  Working together would stop such anomalies. Another good reason to partner with finance was the department’s ability to forecast headcount and its data abilities.

But creating this partnership meant tying together unconnected processes, misaligned people data, and sorting out data quality and ownership issues and banishing the silo mentality between the two. Sewell points out:

We were looking at exactly the same things, but from opposite sides. So slowly over time we bought our two data sets together and are now working in partnership.

With the ability to accurately agree on headcount and more importantly forecast headcount, there’s greater control over recruitment.

HSIC has come a long way in a short time and it wasn’t done with the aid of outside consultants or swanky software: it was all achieved using the humble Excel spreadsheet. Sewell says:

We’ve been working on spreadsheets because it’s the easiest tool available to us.

My take

What’s great about the experience of the HSCIC is how the organization ably demonstrates that kicking off HR analytics does not take a massive investment in technology or in resources.

Instead, what it takes is someone with drive and the gumption to just start somewhere. If and when HSCIC does invest in more sophisticated analytics technology, the HR team and their partners will have gained invaluable experience about the power of data.

Sewell was speaking at the CIPD HR analytics conference in London.

    Comments are closed.

    1. Karen Bannan says:

      This case study is a good one, and one that demonstrates the benefits of learning about what other organizations are doing. Another good case study can be found here:

      Overall, I also thought it was telling that the company knows it doesn’t have full use of its data yet. That is still to come!


      Karen J. Bannan, commenting on behalf of IDG and Infomatica.

    2. abhilash bodanapu says:

      This is a rare article written with lot of gut and intuition on Analytics. Thanks for the Insights Janine Milne, its motivating.